Index Catalog // ScholarsArchive@OSU

Correct abstraction in counter-planning : a knowledge compilation approach

Creator:: Flann, Nicholas S.
Abstract:: Knowledge compilation improves search-intensive problem-solvers that are easily specified but inefficient. One promising approach improves efficiency by constructing a database of problem-instance/best-action pairs that replace problem-solving search with efficient lookup. The database is constructed by reverse enumeration- expanding the complete search space backwards, from the terminal problem instances. This approach...
Resource Type:: Dissertation
Full Text:: compilation approach AN ABSTRACT OF THE THESIS OF Nicholas S. Flann for the degree of Doctor of Philosophy

Reaction Pathways of Oxo-Hydroxo Group 5 Clusters to Metal Oxide Thin Films

Creator:: Mansergh, Ryan H.
Abstract:: Oxo-hydroxo Group 5 metal clusters are an untapped resource to study and advance aqueous solution processing of metal oxide thin films. The tetramethylammonium (TMA) hexatantalate salt (TMA6[H2Ta6O19]) yields dense Ta2O5 films (~95% of the bulk ß-Ta2O5 density) with atomically smooth surfaces (<4 Å root mean square surface roughness). This same...
Resource Type:: Dissertation
Full Text:: Ha-Yeon Cheong, David Xiulei Ji, May Nyman, Prasad Tadepalli, and John F. Wager, whose diverse

Nanoparticle-assisted diffusion brazing of metal microchannel arrays : nanoparticle synthesis, deposition, and characterization

Creator:: Eluri, Ravindranadh T.
Abstract:: Microchannel process technology (MPT) offers several advantages to the field of nanomanufacturing: 1) improved process control over very short time intervals owing to shorter diffusional distances; and 2) reduced reactor size due to high surface area to volume ratios and enhanced heat and mass transfer. The objective of this thesis...
Resource Type:: Dissertation

Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

Creator:: Dodge, Jonathan E.
Abstract:: Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
Resource Type:: Dissertation
Full Text:: , Zhengxian Lin, Theresa Mai, Sai Raja, Caleb Matthews, Nicholas Kiddle, Evan Newman, Christopher Perdriau

Inclusive Software Design and Its Methods for Beyond-WIMP User Interfaces

Creator:: Fallatah, Abrar
Abstract:: While digital inclusivity researchers and software practitioners have been trying to address exclusion biases in Windows, Icons, Menus, and Pointers (WIMP) user interfaces (UIs) for a long time, little has been done to investigate if and how inclusive software design and its methods that have been devised for WIMP UIs...
Resource Type:: Dissertation

Semantic embodied navigation : developing agents that navigate from language and vision

Creator:: Krantz, Jacob
Abstract:: Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
Resource Type:: Dissertation

Coordination for Scalable Multiple Robot Planning Under Temporal Uncertainty

Creator:: Marcon dos Santos, Gilberto
Abstract:: This dissertation incorporates coalition formation and probabilistic planning towards a domain-independent automated planning solution scalable to multiple heterogeneous robots in complex domains. The first research direction investigates the effectiveness of Task Fusion and introduces heuristics that improve task allocation and result in better quality plans, while requiring lower computational cost...
Resource Type:: Dissertation

Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

Creator:: Aziere, Nicolas
Abstract:: This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
Resource Type:: Dissertation

Deep Learning for Human and Biological Languages

Creator:: Hong, Junki
Abstract:: We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
Resource Type:: Dissertation

Analytical Methods for Improving Causal Inference

Creator:: Sinha, Meghamala
Abstract:: Causal inference is an important analytical tool to bridge the gap between prediction and decision-making. However, learning a causal network solely from data is a challenging task. In this work, various techniques have been explored for a better and improved causal network learning from data. Firstly, the problem of learning...
Resource Type:: Dissertation

ScholarsArchive@OSU

Correct abstraction in counter-planning : a knowledge compilation approach

Reaction Pathways of Oxo-Hydroxo Group 5 Clusters to Metal Oxide Thin Films

Nanoparticle-assisted diffusion brazing of metal microchannel arrays : nanoparticle synthesis, deposition, and characterization

Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

Inclusive Software Design and Its Methods for Beyond-WIMP User Interfaces

Semantic embodied navigation : developing agents that navigate from language and vision

Coordination for Scalable Multiple Robot Planning Under Temporal Uncertainty

Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

Deep Learning for Human and Biological Languages

Analytical Methods for Improving Causal Inference

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